1. Field of the Invention
The invention relates to an autonomous navigating system having obstacle recognition, in particular an intelligent obstacle recognition adapted to classify the obstacles.
2. Description of the Related Art
Since autonomous navigating systems move without a human driver, such systems must be provided with sensor technology to avoid that the autonomous navigating systems are blocked by obstacles within the traveling path. To achieve this, the obstacle must first be recognized. This is usually done with sensors such as radar or contact sensors, or with the use of image processing systems. When hitting an obstacle, the navigating system is stopped and, as a rule, an evading movement is started to avoid a collision between the autonomous system and the obstacle. Autonomous navigating systems copy the topography they move through on a virtual map on which all obstacles are marked. This virtual map is continuously updated by the sensor data so that disappeared or new occurring obstacles are marked. Each obstacle may be associated with a stationarity value indicating the number of sensor detections the obstacle is in the same position and orientation. Thus, in a long process, the navigating system can, in a sense, learn the stationary obstacles such as walls.
It is the object of the present invention to improve autonomous navigating systems with regard to their handling of movable obstacles.
The present autonomous navigating system comprises a sensor having a contact element for contacting an obstacle, the contact element being prestressed in the direction of movement and movable against the prestressed force, and a detector measuring the change in position of the contact element. In the present case, change in position means that at least a part of the contact element moves, e.g. by displacement or deformation. The sensor provides a sensor signal depending on the change in position to an evaluating device which in turn provides a first obstacle signal characterizing an obstacle not to be moved by the system, when the sensor signal is greater or equal to a limit value, and a second obstacle signal characterizing an obstacle to be moved by the system, when the sensor signal is less than the limit value. In case of a first obstacle signal, the system can either stop or move around the obstacle. In the case of a second obstacle signal, there is an additional option that the system moves on and thereby displaces the obstacle. This type of obstacle recognition has the advantage that the autonomous navigating system directly, i.e. without a long process of learning, recognizes whether an obstacle can be displaced by the system or not. Thus, the obstacle can be categorized immediately upon first detection by the autonomous system. Further, it is not only determined whether a movable or immovable obstacle is present, but whether it can be moved by the autonomous navigating system or not. This increases the range of activities and thereby the range of applications for such an autonomous navigating system.
Under ground conditions that allow only for a poor traction of the system, it may occur that the drive of the system temporarily loses ground contact which would result in a relief of the contact element and, thus, to the assumption that the obstacle can be moved. To avoid such interpretations, the evaluating device may be provided with additional sensor technology that allows for statements on the traction behavior of the system.
Preferably, the evaluating device includes a memory with stored sensor signal curves. By comparing a currently measured sensor signal curve to the sensor signal curves stored in the memory, different obstacles can be differentiated or categorized. With a movable obstacle, the contact element is typically moved against the prestressed force until the force transferred onto the obstacle is sufficient to overcome the static friction of the obstacle. Then, the force will slightly decrease between the system and the obstacle since the obstacle now moves with the lesser sliding friction. Suitable for a comparison of such curves is the point of the highest amplitude which is reached when the static friction is overcome, or the mean amplitude of the sliding friction portion of the sensor signal curve. With obstacles that cannot be moved by the system, it may be determined from the raising signal path up to the limit value, for example, whether the obstacle is elastically deformable. The obstacle is elastically deformable if the sensor signal does not increase linearly.
The sensor may be configured such that at least a part of the contact element is disposed transverse to the direction of movement and is deflectable, the deflectable portion of the contact element being provided with a wire strain gauge as a detector. This allows for a relatively simple and robust mechanical structure, since the contact element itself applies the prestressed force. In the area where an obstacle could be met, the contact element can be provided with an elastic, deformable damping element which reduces the mechanical stress on the sensor, on the one hand, and reduces major deflections of the contact element to the measurement range of the wire strain gauge or allows for an adaptation to obstacles of different weight or different speeds of the system, on the other hand.
In another embodiment, the change in position of the contact element can be measured contactlessly with optical sensors, for example, which is advantageous in that the oftentimes delicate detector is completely uncoupled from the contact element against which the obstacle may hit. This allows for a particularly robust structure of the sensor that can also take harder collisions with an obstacle.